THERMODYNAMICS AND PHASE EQUILIBRIUM OF Cu－Y－O，Cu－Y－S，Cu－Y－O－S LIQUID SOLUTIONS

ＴＨＥＲＭＯＤＹＮＡＭＩＣＳＡＮＤＰＨＡＳＥＥＱＵＩＬＩＢＲＩＵＭＯＦＣｕ－Ｙ－Ｏ，Ｃｕ－Ｙ－Ｓ，Ｃｕ－Ｙ－Ｏ－ＳＬＩＱＵＩＤＳＯＬＵＴＩＯＮＳ￥Ｄｕ，Ｔｉｎｇ；Ｌｉ，Ｇｕｏｄｏｎｇ（ＣｅｎｔｒａｌＩｒｏｎａｎｄＳｔｅｅｌＲｅｓｅａｒｃｈｉｎｓｔｉｔ...     

隔直电容在弧焊逆变器中抗偏磁能力的分析

本文采用状态平均法建立了隔直电容在知式焊接逆变器中抗偏磁的动态模型，并进行了动态分析，为焊接逆变器的设计提供了理论依据。     

Generalized incremental frequency method for topological designof continuum structures for minimum dynamic compliance subject to forced vibration at a prescribed low or high value of the excitation frequency

The application of multidisciplinary design optimisation is mostly confined to bi-disciplinary systems such as fluid-structure interaction problems. High fidelity models of three disciplines involving electromagnetic-thermal-structural designs are rare. Here, the multidisciplinary optimisation of such a design is presented. The device comprises a C-shaped iron core and a single coil. The problem is decomposed using a monolithic multidisciplinary feasible architecture. The multidisciplinary analyses involve a single three-dimensional finite element mesh for transient non-linear electromagnetic, non-linear-static thermal, and linear-static structural models. During each multidisciplinary iteration the mesh is linearly morphed. A gradient based optimisation algorithm in combination with a multi-start routine is applied to the constrained mass minimisation problem. Multidisciplinary feasibility is ensured by convergence of a single coupling parameter i.e. air-gap deformation. In conclusion, some multidisciplinary optimisation, analyses, and decomposition considerations are discussed.     

信息安全策略实施困难的原因与对策分析

随着企业生产规模的扩大,其所掌控的资产也越来越多。信息作为企业重要的资产,其安全性正得到越来越多的企业的关注,很多企业为了保证自身信息的安全与保密性,也制订了自身的信息安全策略。然而,很多企业的信息安全策略常常形同虚设,没有发挥其应有的作用,甚至存在着严重的漏洞,为企业的健康发展埋下了不小的隐患。笔者结合自身多年的工作经验,就企业信息安全策略实施过程中存在的问题进行分析,并针对性的提出几点对策,希望对相关人士能有所帮助。     

Bounded Consensus Algorithms for Multi‐Agent Systems in Directed Networks

In this paper, the consensus problem is investigated via bounded controls for the multi‐agent systems with or without communication. Based on the nested saturation method, the saturated control laws are designed to solve the consensus problem. Under the designed saturated control laws, the transient performance of the closed‐loop system can be improved by tuning the saturation level. First of all, asymptotical consensus algorithms with bounded control inputs are proposed for the multi‐agent systems with or without communication delays. Under these consensus algorithms, the states’ consensus can be achieved asymptotically. Then, based on a kind of novel nonlinear saturation functions, bounded finite‐time consensus algorithms are further developed. It is shown that the states’ consensus can be achieved in finite time. Finally, two examples are given to verify the efficiency of the proposed methods.     

基于模糊理论的非处方药的满意度评价系统

为了帮助顾客从众多对症的非处方药中选出最满意的药品,提出了开发1个基于Web的非处方药满意度评价系统。系统根据顾客提供的典型症状,采用疾病与症状相结合的选药策略,查找出所有对症的非处方药,并以药品安全性、疗效、稳定性、易用性、价格作为评价因素,根据顾客的关注角度和关注程度确定各因素权重,用模型b=W·R对对症药品进行满意度评价,按满意度高低依次推荐。经实际应用,系统推荐准确度在70%以上。     

Single image super-resolution using global enhanced upscale network

Current works on super-resolution have obtained satisfactory results since the advance of the convolution neural network. Nevertheless, most previous works use one network for one integer scale factor so ignore the super-resolution of the arbitrary scale factor. In this work, we propose a novel approach called Global Enhanced Upscale Network (GEUN) to tackle super-resolution with a single model adapting the arbitrary scale factor. In our GEUN, we propose the Global Enhanced Upscale module to replace the conventional upscale module. Our GEUN can upscale low-resolution images with an arbitrary scale factor through only one model. Extensive experimental results demonstrate the superiority of our GEUN.

     

Analysis of Internet Financial Risks Based on Deep Learning and BP Neural Network

Computational Economics - The study aims to analyze and forecast Internet financial risks based on the model based on deep learning and the Back Propagation Neural Network (BPNN). First, the theory...     

Exploring Statistical Arbitrage Opportunities Using Machine Learning Strategy

Computational Economics - Arbitrage opportunity exploration is important to ensure the profitability of statistical arbitrage. Prior studies that concentrate on cointegration model and other...